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Ecotoxicology and Human Environmental Health

Dynamic Oxidative Potential of Atmospheric Organic Aerosol under Ambient Sunlight Huanhuan Jiang, and Myoseon Jang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00148 • Publication Date (Web): 17 May 2018 Downloaded from http://pubs.acs.org on May 17, 2018

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Environmental Science & Technology

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Dynamic Oxidative Potential of Atmospheric Organic Aerosol under Ambient Sunlight

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Huanhuan Jiang† and Myoseon Jang†*

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†

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Infrastructure and Environment, University of Florida, Gainesville, FL 32608, USA

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Correspondence to: Myoseon Jang ([email protected])

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ABSTRACT

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The atmospheric process dynamically changes the chemical compositions of organic aerosol (OA),

8

thereby complicating the interpretation of its health effects. In this study, the dynamic evolution of the

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oxidative potential of various OA was studied, including wood combustion particles and secondary

10

organic aerosols (SOA) generated from different hydrocarbons (i.e. gasoline, toluene, isoprene and α-

11

pinene). The oxidative potential of OA at different aging stages was subsequently measured by the

12

dithiothreitol consumption (DTTm, mass normalized). We hypothesized that DTT consumptions by

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OA were modulated by catalytic particulate oxidizers (e.g., quinones), non-catalytic particulate

14

oxidizers (e.g., organic hydroperoxides and peroxyacyl nitrates) and electron-deficient alkenes. The

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results of this study showed that the oxidative potential of OA decreased after an extended period of

16

aging due to the decomposition of particulate oxidizers and electron-deficient alkenes. Quinones (GC-

17

MS data) partially attributed to the DTTm of fresh wood smoke particles but rapidly dropped with

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aging. In biogenic SOA, organic hydroperoxides (4-nitrophenyl boronic acid assay) exclusively

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accounted for DTTm and decreased with aging. The DTTm of aromatic SOA, mainly comprising

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organic hydroperoxides and electron-deficient alkenes (FTIR data), was shortly elevated during the

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early atmospheric process, however, showed a noticeable decrease (32-75%) for a long period of

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aging. We concluded that fresh or moderately aged OA are more reactive to a sulfhydryl group than

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highly aged OA.

Department of Environmental Engineering Sciences, Engineering School of Sustainable

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ACS Paragon Plus Environment


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TOC figure

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1. INTRODUCTION

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Exposure to particulate matter (PM2.5, aerodynamic diameter < 2.5 µm) has been implicated in the

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detrimental cardiovascular and pulmonary diseases (e.g. asthma, and myocardial infarction).1-3

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Organic aerosol (OA) comprises a substantial fraction (20-90%) of PM2.5,4 however, the health effect

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of OA remains unknown. OA is a complex mixture of organic compounds and contains a large fraction

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of particulate oxidizers, which may react with cellular antioxidants (e.g. glutathione peroxidase-1;

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GSH), thereby interrupting the oxidative balance and leading to a cascade of oxidative stress

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responses.5

34

A chemical assay using dithiothreitol (DTT), a surrogate of biological reducing agents, has been

35

widely applied to measure the capability of PM2.5 to oxidize cellular materials. Catalytic particulate

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oxidizers like quinones can efficiently oxidize DTT through a redox cycle and have been recognized

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as the major contributors to the oxidative potential of PM2.5.6, 7 However, the fraction of quinones in

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OA is low, especially in secondary organic aerosols (SOA).8-11 Our previous studies have reported the

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importance of non-catalytic oxidizers (e.g. organic hydroperoxides (OHP) and peroxyacyl nitrates

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(PAN)) and electron-deficient alkenes in DTT responses of OA.12, 13 Congruently, OHP (including

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alkyl hydroperoxides and acyl hydroperoxides) and PAN can oxidize DTT to disulfides, sulfenic acids,

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sulfinic acids or sulfonic acids through non-catalytic reactions.14, 15 An electron deficient alkene is

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defined as the C=C (alkene) double bond coupled with an electron withdrawing group, such as a

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carbonyl, a nitro, and a carboxylic acid.16 An electron-deficient alkene can react with a sulfhydryl

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group in DTT via a Michael addition.16

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The fraction of particulate oxidizers in OA can be dynamically changed by the atmospheric process.

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During the initial aging process of hydrocarbons (HC) or OA, the molecular weight and the oxidation

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state of aerosol products presents an increase owing to the addition of oxygenated functional groups.

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After a long aging period, high-volatility compounds begin to form through the fragmentation of low-

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volatility compounds.17 The impact of the aging process on particulate oxidizers of OA has been

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studied using state-of-art techniques such as chemical ionization mass spectrometers and aerosol mass

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spectrometers.18 These studies, however, were limited to the tentative analysis of stable products due

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to the lack of standards and the instability of particulate oxidizers under high operation temperature of

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these instruments.

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The current work studied the aging effect on the oxidative potential of OA and its chemical

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compositions. OA is either derived from wood combustion smoke or produced from the

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photooxidation of HCs (i.e. gasoline, toluene, isoprene and α-pinene) in a large outdoor smog

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chamber. Gasoline, a highly volatile mixture of C4-C9 HCs, can easily evaporate into the atmosphere,

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and makes a large contribution (~4 Tg/yr) to global SOA.19 Wood combustion particles, containing a

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large amount of organic mass (e.g. oxygenated HCs and substituted aromatic HCs.), constitute 14% -

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30% of primary fine particles in the urban air.20-22 The oxidative potential of OA at different aging

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stages was measured using DTT assay. In order to study the significance of quinones in the oxidative

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potential of OA and their stability with photochemical aging, quinones in wood smoke particles and

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gasoline SOA were measured by gas-chromatography mass-spectrometry (GC-MS) over the course

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of the chamber experiment. OHP and PAN compounds in OA were quantified using 4-nitrophenol

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boronic acid (NPBA) assay and Griess assay, respectively. The abundance of electron-deficient

67

alkenes was analysed using a Fourier Transform Infrared (FTIR) spectrometer.

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2 MATERIALS AND METHODS

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2.1 Outdoor chamber experiments

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The photooxidation of HCs and wood smoke experiments were conducted at the University of Florida

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Atmospheric Photochemical Outdoor Reactor (UF-APHOR) with dual chambers (52 m3 each). The

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chambers were flushed using the clean air generated from the air purifiers (GC Series, IQAir) for two

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days prior to each experiment. Wood burning smoke particles were generated under either open-fire

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combustion (250 °C) or smoldering combustion (150 °C) using commercial hickory hardwood. For

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the experiments to form SOA from HCs (i.e. gasoline, toluene, isoprene, and α-pinene), liquid HC was

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injected into the chamber using a glass manifold with clean air. CCl4 was also introduced to monitor

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the chamber dilution. The desired volume of NO (2% in N2, Airgas) was injected using a syringe

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through the injection port connected to the chamber. All chemical species were introduced to the

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chamber before sunrise. A gas chromatography-flame ionization detector (HP 5890) was applied to

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measure the concentrations of HCs and CCl4. Concentrations of NOx and O3 were monitored using a

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chemiluminescence NO-NOx analyzer (Model 200 E) and a photometric O3 analyzer (Model 400 E),

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respectively. The relative humidity (RH) and temperature were measured using a hygrometer (the

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Campbell Scientific, CS215-L). The sunlight intensity was monitored inside the chamber using the

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ultraviolet radiometer (TUVR, the Eppley Laboratory, wavelength 290-385 nm). Particle number

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concentration was monitored using a scanning mobility particle sizer (SMPS, TSI, Model 3080)

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coupled with a condensation nuclei counter (TSI, Model 3025A and Model 3022). The particle number

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concentration was converted to the mass concentration using the density of OA (1.3 g cm-3 for -

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pinene SOA and 1.4 g cm-3 for other OAs).11, 23, 24 The experimental conditions and SOA yields are

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listed in Table 1. The time profiles of concentrations of OA mass, NOx, NO, and O3 are shown in

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Figure S1.

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2.2 Sampling and extraction methods

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A particle-into-liquid sampler (PILS) coupled with a carbon denuder (to remove gaseous compounds)

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was utilized to collect particles within a small amount of water at an air flow rate of 13 L/min.25 The

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PILS collection efficiency is larger than 95% for particles in this study.25 The PILS samples were

95

subsequently applied to the chemical assays described in Section 2.3.

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The Teflon filter (13 mm diameter, Pall Life SciencePallflex, type TX40HI20-WW) was applied to

97

collect wood smoke particles or gasoline SOA at a flow rate of 28 L/min with the use of a pump.

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Immediately after sampling, a 10-L of internal standard, comprising of six deuterated PAHs, was

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added to the filter. The details of the internal standard can be found in Section S2.1, Supporting

100

Information (SI). The particles were then incubated in 20 mL methylene chloride for 6 h at room

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temperature to extract the organic compounds. Metals and black carbon were excluded due to their

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poor solubility in methylene chloride. The extraction efficiency of particles was about 40-80%, which

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was estimated using the filter mass before and after solvent extraction. The filter-extract was

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subsequently concentrated to 0.3 mL using dry air, transferred to a GC vial, and applied to the GC-

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MS analysis.

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2.3 Chemical assays

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The QA/QC data of DTT assay, OHP analysis, and PAN analysis can be found in our previous study.13

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The DTT measurement of wood smoke particles utilized the filter-extract samples, and all other

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chemical analysis used the PILS samples.

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2.3.1 DTT assay

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The oxidative potential of OA was measured using the DTT assay. A reaction mixture of 1.9 mL filter-

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extract or PILS sample, 0.6 mL potassium phosphate buffer (25 mM), and 0.5 mL DTT (0.875 mM)

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was incubated at 37 °C and continuously shaken using an Edison Environmental Incubator Shaker

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(G24) at a low shaking speed. After a specific incubation time (t, ranging from 50 min to 280 min), a

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0.5-mL of the reaction mixture was withdrawn and transferred to another vial, in which 0.5 mL

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trichloroacetic acid (1% w/v; the quenching reagent) was previously added. Then, 0.5 mL DTNB (1

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mM) and 0.5 mL Tris-base buffer (0.4 M, pH=8.9) were added to the quenched mixture. The residual

118

DTT in the quenched mixture reacted with DTNB to form a yellow-color product, 2-nitro-5-

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thiobenzoic acid, which presents a high molar extinction coefficient (14150 M−1 cm−1) at 412 nm

120

wavelength. The absorbance of the final mixture at 412 nm was measured using a UV/Vis

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Spectrometer (Lambda, PerkinElmer). Positive controls (0.25 μM PQN) and blank controls (DI water)

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were run in duplicates for each set of DTT measurements. The blank-corrected DTT consumption by

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OA (∆DTTOA, nmol) was calculated using the absorbance of DTT-blank mixture without incubation

124

(A0), the absorbance of DTT-blank mixture after incubation (Ablk), the absorbance of DTT-OA mixture

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(AOA) after the reaction, and the initial DTT concentration (DTT0, nmol). ∆DTTOA =

126 127

Ablk -AOA A0

DTT0

(1)

The mass-normalized DTT consumption, DTTm, is defined as, DTTm =

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∆DTTOA mOA

(2)

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where mOA is the OA mass applied to the DTT measurement. The DTT consumption was restricted

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within 50% of the initial DTT concentration by constraining the OA mass added to the reaction

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mixture.

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2.3.2 OHP analysis

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1 mL PILS sample was incubated with 100 μL NPBA solution (10 mM in methanol), and 900 μL

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KOH (50 mM) at 85 °C for 7 h. NPBA reacted with OHP to form a yellow-color product, 4-

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nitrophenol, which presents a large molar extinction coefficient (18000 M−1 cm−1) at 406 nm. Positive

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controls (20 μM H2O2) and blank controls (DI water) were run in duplicates for each set of

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measurements.

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2.3.3 PAN analysis

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PAN type compounds in 300 μL PILS sample were firstly hydrolyzed by adding 300 μL KOH (50

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mM) to form nitrites. Then, 1 mL Griess reagent (a mixture of 20 mM sulfanilic acid and 5 mM n-(1-

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naphthyl)ethylenediamine dihydrochloride) was added to react with nitrites forming azo dyes that

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could be quantified based on their absorbance at 541 nm wavelength. Positive controls (10 μM NaNO2)

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and blank controls (DI water) were run in duplicates for each set of measurements.

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2.4 GC-MS analysis

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Quinone compounds were analyzed using GC-MS. A 10-L of recovery standard (Section S2.2) was

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added to each GC vial before GC-MS analysis. A 1-μL filter-extract sample was injected in on-column

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mode to a Varian CP-3800 gas chromatograph interfaced with a Varian Saturn 2200 mass

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spectrometer. The column oven temperature was held at 45 °C for 0.5 min; then ramped to 100 °C by

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a 15 °C/min gradient and held for 2.5 min; and finally ramped to 280 °C with a 12 °C/min and held

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for 8 min. The individual compounds in particle extracts were identified using an external standard

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(Section S2.3) and tentatively analyzed using the National Institute of Standards and Technology

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(NIST) library. Only PQN and anthraquinone (AQN) were detected in the wood smoke particles.

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2.5 FTIR analysis

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The functionalities in toluene SOA was analyzed using an FTIR (Nicolet Magma 560, Madison, WI,

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USA). The chamber particles were collected on a silicon FTIR disc (13 × 2 mm, Sigma–Aldrich, St

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Louis, MO, USA) by impaction. The mass of collected particles was determined by measuring the

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FTIR disc mass before and after the sampling.

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3 RESULT AND DISCUSSION

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3.1 The effect of the atmospheric process on the oxidative potential of OA

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Traditionally, catalytic particulate oxidizers such as quinones in PM have been of wide interest due to

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their high production of ROS through catalytic processes.5 Assuming the pseudo-first order reaction

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of the DTT consumption by quinones, DTTm should linearly increase with reaction time t and the

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mass-normalized consumption rate of DTT should be constant.12 Hence, mass-normalized DTT

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consumption rate has been used to represent the oxidative potential of PM. However, if DTT is

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consumed via a non-catalytic process, DTTm is nonlinear to t.

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Figure 1 (1a-1b) and Figure 2 (2a-2b) illustrate the oxidative potential (DTTm) of various OA at

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different aging stages. As shown in Figure 1a, for freshly generated wood combustion OA, the DTTm

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of both high-temp and smoldering wood samples increased linearly with t, thereby suggesting that the

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DTT consumption originated mainly from the catalytic processes of quinones. However, the

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relationship between DTTm vs. t became deviated from linearity as wood smoke particles aged, thus

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suggesting that the DTT consumption was dominated by non-catalytic processes. Additionally, DTTm

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dropped by 52% for high-temp wood particle samples after a 9-h aging, and 74% for smoldering

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samples after a 7-h aging (Figure 1b). 9



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As shown in Figure 2a, the DTTm of gasoline SOA was found to be nonlinear to t during the entire

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period of SOA formation. It has been evidenced that gasoline SOA is mainly formed from the

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photooxidation of mono-aromatic ring HCs, such as toluene, (o, m, p)-xylene, 1,3,5-trimethylbenzene

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and 1,2,4-trimethylbenzene.26 Hence, in order to understand the behaviour of DTTm of aromatic SOA,

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the DTTm of toluene SOA produced under two different NOx conditions was measured. HNOX-

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toluene SOA showed a slightly higher DTTm than LNOX-toluene SOA (Figure 2a). Similar to gasoline

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SOA, the DTTm values of all toluene SOA samples were nonlinear to t. This implicates that DTTm

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was governed by non-catalytic DTT-reactive compounds. Additionally, as illustrated in Figure 2b, The

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DTTm of both gasoline and toluene SOA were influenced by the aging process. A 32% reduction in

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gasoline DTTm occurred after a 6-h aging. DTTm of HNOX-toluene SOA presented an increase in

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early aging time (before noontime) and then a sharp decrease (up to 50%) as SOA further aged in the

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afternoon. For LNOX-toluene, a significant decrease (up to 75%) of DTTm appeared over the course

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of the chamber experiment.

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Figure 2 also shows the DTTm of isoprene SOA and α-pinene SOA. The DTTm of biogenic SOA was

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nonlinear to t (Figure 2a) as expected in that there are no quinone products in biogenic SOA. Within

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our sampling period, a slight decrease of DTTm was observed between 12:15 and 14:25 for HNOX-

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isoprene SOA and a noticeable drop of DTTm appeared between 10:40 to 13:00 for LNOX-α-pinene

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SOA (Figure 2b).

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3.2 Evolution of particulate oxidizers

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To decipher the DTT consumptions by various OA, the chemical characteristics of particulate

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oxidizers in OA were determined. It was observed that the atmospheric process lead to the dynamic

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evolution of particulate oxidizers. As expected, quinones were revealed to be only significant in fresh

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wood smoke OA, but not in other OA. A considerable amount of OHP appeared in all OA, and OHP

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in SOA showed a dramatic reduction with a long-period aging process. However, the formation of

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PAN was insignificant in all the OA studied.

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3.2.1 Particulate oxidizers in wood combustion OA

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The time profiles of quinones (PQN+AQN) in wood smoke particles were determined using GC-MS

201

analysis (Figure 3). There was a large amount of quinones in fresh wood smoke OA, which can well

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explain the linear increase of DTTm with t (Figure 1a). Compared to quinones (65 pmol/μg) in fresh

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smoldering OA, a higher concentration of quinones (80 pmol/μg) was observed in fresh high-temp

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OA. This result is in parallel with the higher DTTm as observed in fresh high-temp OA (Figure 1a).

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However, as particles aged, the concentrations of quinones presented a dramatic drop to a negligible

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amount, congruent to the nonlinearity between DTTm and t (Figure 1a). The aging effect on wood

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smoke particles has also been reported by Zhong et al. who observed a bleaching of chromophores

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(e.g. quinoids and phenols) with the progression of photooxidation. Quinones such as AQN can be

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photooxidized and decomposed to substituted-phenols, substituted-benzaldehydes, and ring-opening

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products with aging (Figure S2).27, 28

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Non-catalytic particulate oxidizers in wood smoke were also determined. As shown in Figure 1b, there

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was about 2 nmol/μg of OHP detected in wood smoke OA, and the OHP showed no significant change

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for long periods of aging. OHP contributed to 12-24 % of DTTm for high-temp wood samples and 28-

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78 % for smoldering samples (Figure 1c). Nevertheless, there were still unexplainable DTTm

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outcomes. For example, there was a large gap between DTTm and OHP in aged wood smoke particles,

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implicating the existence of other non-catalytic DTT-active species. Wood combustion has been

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reported to produce a large fraction (36-42%) of aromatic compounds,29 which can generate electron-

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deficient alkenes through the photooxidation.8,

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partially attributed to these electron-deficient alkenes. The importance of electron-deficient alkenes in

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wood smoke particles needs to be investigated further.

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3.2.2 Particulate oxidizers in gasoline SOA and toluene SOA

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Quinones were not detected in gasoline SOA (GC-MS data not shown).26 The quantity of OHP in

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aromatic SOA showed an increase in the morning while a noticeable decrease in the afternoon. For

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example, OHP in gasoline SOA increased from 2.3 nmol/μg (9:00) to 3.2 nmol/μg (11:30) and dropped

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back to 2.2 nmol/μg (14:40). OHP in HNOX-toluene SOA increased from 2.3 nmol/μg (10:20) to 3.5

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nmol/μg (12:30) and dropped to 1.2 nmol/μg (17:00). The quantity of PAN in aromatic SOA, though

227

insignificant, showed a similar trend to OHP with aging. The concentration of organic peroxides

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(ROOR and OHP) in SOA formation have also been measured in other studies using the iodometric-

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spectrophotometric method. For example, Sato et al. reported a 17 wt % of organic peroxides in

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LNOX-toluene SOA. However, the NPBA assay with a high accuracy and robustness has been for the

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first time used to measure the OHP solely in our studies.13

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The increases of both OHP and PAN in the early stage of the aging process should be ascribed to the

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functionalization in the photooxidation products formed from aromatic HCs, as shown in reactions

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SR1-SR7, SI.31 Conversely, the decay of OHP and PAN can be explained by photolysis (reactions

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SR8 and SR9),32,

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(Scheme S1 and S2),10, 35, 36 or in-particle chemistry with other aerosol products (Schemes S3).37 The

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rate constant and corresponding half-life with respect to the decomposition of selected OHP and PAN

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compounds are summarized in Table S1.13, 32-35, 38-41 PAN is thermally unstable with a half-life ranging

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from 49 min to 55 min at 298 K.34 The reaction of PAN with OH is unimportant given its extremely

33

30

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DTTm of wood combustion particles could be

thermal decomposition (reactions SR10-15),34 the reaction with OH radicals

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low rate constant (e.g. 310-14 cm3/molecule/s for CH3C(O)OONO2 + OH).33 However, the major sink

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of OHP is attributed to its reaction with OH radicals. For example, the attack of TLBIPEROOH (a

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secondary product from the photooxidation of toluene) by OH radicals leads to a half-life of 35 min

243

at 298 K.35, 36 The OHP may also be attacked by a carbonyl group via a Baeyer–Villiger reaction

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(Scheme S3).37 This reaction has been evidenced to be more preferable for aldehydes than ketones.37

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Multifunctional products containing both an aldehyde and a hydroperoxide group are abundant in

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toluene SOA and may allow the rapid intra-molecular reaction of a hydroperoxide with an aldehyde,

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leading to a rapid reduction of DTTm with aging.

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However, DTTm of aromatic SOA with aging can only be partially attributed to OHP and PAN. For

249

example, as shown in Figure 2c, OHP (mostly) and PAN together contributed only 23-38% to DTTm

250

in LNOX-gasoline, 22-35% in HNOX-toluene, and 25-73% in LNOX-toluene. Hence, the source of a

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large fraction of DTT response remained uncertain. We hypothesized that electron-deficient alkenes

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that could react with DTT through a Michael addition could be major contributors to DTTm of aromatic

253

SOA. Electron-deficient alkenes refer to the alkenes coupled with electron-withdrawing groups (e.g.

254

carbonyl and nitrates) and are commonly found in ring-opening products from the photooxidation of

255

mono-ring aromatic HCs (Scheme S4).42, 43 To confirm their significance in DTTm, electron-deficient

256

alkenes in toluene SOA were quantified using FTIR analysis. Figure 4a shows the concentrations of

257

functionalities (C-H, O-H, C=O, C(=O)O-H, CH=CH) in LNOX-toluene SOA (mid-collection time

258

of 15:00) that were estimated by decoupling the FTIR spectrum (Figure S3 and Table S2)42, 44. The

259

mass fraction of OHP in LNOX-toluene SOA at 15:00 was estimated based on interpolation of OHP

260

values in Figure 2b. The signal of organonitrate (1645 cm-1, 1559 cm-1, and 1340 cm-1) 42 in the FTIR

261

spectrum was found to be negligible. Thus, we assumed that most C=C groups were conjugated with

262

electron-withdrawing groups such as C=O and C(=O)O-H. This assumption was also supported by the 13



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alkene products, which were simulated using the MCM mechanism for toluene photooxidation.35, 36

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The total mole concentration of electron-deficient alkenes in LNOX-toluene SOA was estimated to be

265

up to 5.0 nmol/μg-SOA, which can completely account for the gap between DTTm and OHP+PAN

266

(Figure 4b). Hence, we imply that electron-deficient alkenes are important contributors to DTTm of

267

toluene SOA, and presumably to that of gasoline SOA. The decrease of the gap between DTTm and

268

OHP+PAN with a long period of aging thus can be inferred to have been caused by the decomposition

269

of electron-deficient alkenes during further photooxidation processes (Table S1 and Scheme S5).35, 36,

270

45

271

3.2.3 Particulate oxidizers in biogenic SOA

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The double bond structures in isoprene and α-pinene are rapidly oxidized by OH radicals or ozone in

273

the first stage of photooxidation,10, 46-49 thus leading to a low production of electron-deficient alkenes.

274

Instead, biogenic SOA contains high concentrations of OHP compared to wood smoke particles and

275

aromatic SOA. As shown in Figure 2c, DTTm of both isoprene and α-pinene SOA were exclusively

276

attributed to OHP (mostly) and PAN. The decrease of DTTm with the photochemical aging was also

277

in conjunction with the decrease of OHP. In detail, the concentration of OHP in HNOX-isoprene SOA

278

was about 5.2 nmol/g at 12:15 (1st sample) with a slight drop in 2 h after the 1st sample, and that of

279

LNOX-α-pinene SOA was 7.3 nmol/g at 10:40 (1st sample) with a dramatic drop to 3.8 nmol/g in

280

3 h after the 1st sample. The decomposition of OHP, as explained in Section 3.2.2, was largely

281

dependent on the reaction pathway via the attack by OH radicals. Correspondingly, Surratt et al.

282

quantified the organic peroxides in LNOX-isoprene using the iodometric-spectrophotometric method

283

and reported a reduction of organic peroxides in aged SOA.50 The amount of PAN (Figure 2b) was

284

extremely low in HNOX-isoprene SOA due to the high volatility of low-molecular-weight PAN-type

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compounds in isoprene SOA (e.g. 0.5 Torr for peroxy methacrylic nitric anhydride).51 However, PAN

286

compounds in LNOX-α-pinene SOA have a relatively high concentration (0.60 nmol/g at 10:40, and

287

0.44 nmol/g at 13:05), probably attributed to their low vapor pressure (ranging from 10-7 to 10-3

288

torr).52

289

4 ATMOSPHERIC IMPLICATIONS.

290

Traditionally, the mass-normalized DTT consumption rate has been measured to represent the

291

oxidative potential of catalytic particulate oxidizers (e.g. quinones), which lead to a linear increase of

292

DTT consumption with reaction time. However, the oxidative potential can also be processed by non-

293

catalytic DTT-reactive compounds in PM. Correspondingly, when the DTT consumption rate is not

294

constant with reaction time, it can mislead the interpretation of oxidative ability of PM. Thus, in order

295

to discern the source of oxidative potential, the mass-normalized DTT consumption (DTTm) of various

296

OA was measured with an extended reaction time, as demonstrated through this study. Only in fresh

297

wood smoke aerosol, DTTm presented a linear increase with reaction time due to quinones (Figure 1a).

298

For other OA including aged wood smoke and all SOA (Figures 1a and 2a), DTTm was nonlinear to

299

reaction time, thus evidently showing that DTTm was mostly or completely promoted by non-catalytic

300

DTT-reactive compounds. Hence, we suggest that DTTm is more suitable to scale the oxidative

301

potential of a variety of OA than the mass-normalized DTT consumption rate.

302

To understand the mechanistic role of OA in bearing the oxidative potential, the concentrations of

303

non-catalytic particulate oxidizers (i.e., OHP and PAN) and electron-deficient alkenes were quantified

304

using acellular assays or FTIR spectral data. In biogenic SOA, nearly 100% of DTTm was attributed

305

to OHP (Figure 2c). For toluene SOA, in addition to OHP, electron-deficient alkenes were also

306

important to increase DTTm. For example, in the LNOX-toluene SOA of this study, electron-deficient 15



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307

alkenes and OHP accounted for up to 67% and 37% of DTTm, respectively. Correspondingly, electron-

308

deficient alkenes may also significantly contribute to DTTm of wood smoke particles and gasoline

309

SOA. Through this study, a dynamic evolution of DTTm was observed with the photochemical aging

310

(Figures 1b and 2b). Highly aged particles were found to be less reactive to the sulfhydryl group of

311

DTT than the fresh or moderately aged particles (Section 3.1), corresponding to the decrease of

312

particulate oxidizers (i.e., quinones, OHP, and PAN) and electron-deficient alkenes (Figures 1b, 2b,

313

3, S2, Reactions SR8-15, Schemes S1-3 and Table S1). In the recent laboratory study, Krapf et al.

314

reported that a significant amount of peroxide-containing oxygenated products was formed from

315

ozonolysis of terpenes but these products were thermodynamically unstable (a lifetime in an order of

316

hours).53 Additionally, the further oxidation of electron-deficient alkene products (Scheme S5 and

317

Table S2) could also partially attribute to the decrease of the DTTm of OA such as wood smoke

318

particles and aromatic SOA, but more direct evidence is needed to prove the importance of electron-

319

deficient alkenes in the DTTm of aromatic-related SOA. In general, oxidative potential induced by PM

320

is indirectly linked to the toxicity of PM as it can cause disorders in cellular signaling cascades, the

321

development of inflammation, allergic responses and other respiratory diseases.54, 55 Based on our

322

results, the toxicity of fresh or moderately aged OA may be greater than that of highly aged OA. The

323

formation and the decay of particulate oxidizers and electron deficient alkenes of this study could

324

severely affect the interaction of OA with health because these chemical species are major contributors

325

to SOA mass in ambient air.

326

The atmospheric environment in rural areas is mostly influenced by biogenic SOA, which has a high

327

yield of OHP. While, conversely in urban areas the exhausted air plumes from gasoline- and diesel-

328

powered motor vehicles are significant sources of primary OA (POA) and SOA precursors.56, 57 It has

329

been estimated that motor vehicles contributed to 2.9±1.6 Tg-SOA/yr in the U.S. with a total urban 16


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330

emission of 3.1 Tg-SOA/yr,56 apparently suggesting that aromatic SOA is important in urban areas.

331

Especially, the study of SOA from gasoline-powered motor vehicles has emerged to be as a critical

332

imperative in recent years because of two reasons. First, the emissions of SOA precursors and POA

333

from diesel-powered motor vehicles are largely reduced due to the application of catalyzed diesel

334

particulate filters.56 Second, the OA derived from a gasoline vehicle is dominated by SOA based on

335

recent chamber studies.56 Typically, the ambient OA under the urban atmosphere consists of various

336

carbonaceous species originating from different aging stages including freshly formed species,

337

moderately aged species and highly oxidized species due to the hydrocarbons continuously emitting

338

from anthropogenic sources. Unlike the ambient air, chamber studies allow to measure the time series

339

of the oxidative potential of OA, although only limited types of aromatic or gasoline SOA can be

340

studied at a given NOx condition. Our studies of gasoline SOA, the characterization of DTTm and SOA

341

compositions, augment the understanding of the toxicity of PM produced in urban areas.

342

The implication of this study is not limited to the oxidative potential of organic compounds in aerosol

343

phase. Given the high abundance of DTT-active species in the gas phase, the oxidative potential of

344

gas-phase organic compounds should also be emphasized. For example, our previous study reported

345

that the concentration of PAN in the gas phase of the isoprene+NOx system was 200 times higher than

346

that in SOA.13 Correspondingly, the concentration of OHP and electron-deficient alkenes in gas phase

347

would also be high. Using the mathematical model, Davies reported that gaseous compounds can be

348

efficiently absorbed in the upper respiratory system (nearly 100%) due to their high diffusion

349

coefficients.58 Excess amounts of gaseous compounds beyond the clearance capacity of mucus in the

350

upper respiratory system, present a risk of being transported into the bloodstream and reaching the

351

heart. The toxicological evidence is mounting that non-catalytic oxidizers are able to bind to the

352

nucleophiles or nucleophilic sites in biomolecules, resulting in the DNA damage and the modification 17



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353

of proteins and lipids.59 For example, tert-butyl hydroperoxide, an OHP, is known to damage cells

354

through either lipid peroxidation or the depletion of glutathione.59, 60 Conjugated carbonyls has also

355

been recognized to induce toxicity in cellular materials through the formation of adducts with cysteine

356

sulfhydryl groups in functional proteins or guanine residues in DNA.61, 62 Hence, studies on the toxicity

357

of both gas-phase and particle-phase non-catalytic oxidizers and electron-deficient alkenes are needed

358

in future.

359

ASSOCIATED CONTENT

360

Supporting Information

361

The profiles of NOx, O3, temperature, and relative humidity in the outdoor chamber experimental

362

section; the workup procedures for GC-MS analyses; the evolution mechanisms of AQN, particulate

363

oxidizers and electron-deficient alkenes, the summary of the kinetic rate constant of the decomposition

364

processes of non-catalytic oxidizers and electron-deficient alkenes, the FTIR spectrum of LNOX-

365

toluene SOA, the functional group composition of LNOX-toluene SOA.

366

AUTHOR INFORMATION

367

Corresponding author

368

*Phone: +1-352-846-1744; fax: +1-352-392-3076; e-mail: [email protected].

369

ORCID

370

Huanhuan Jiang: 0000-0002-5581-375X

371

Myoseon Jang: 0000-0003-4211-7883

372

Notes. The authors declare that they have no conflict of interest.

373

ACKNOWLEDGEMENTS.

18


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374

The authors acknowledge the award from the Ministry of Science and ICT, the Ministry of

375

Environment, the Ministry of Health and Welfare (2017M3D8A1090654) and the award from the

376

National Institute of Metrological Sciences (KMA2018-00512).

377

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378 Table 1. Outdoor chamber experiment conditions. 379 Date and Experiment Condition b [HC]0 c [NOx]0 e OAmax Y RH g Temp g Chemical analysis h a Chamber (HONO) ppmC ppb µg/m3 % % K d 04/12/17 E Wood smoke High-Temp N/A N/A 2100 N/A 13-55 287-315 DTT,OHP,PAN,GC-MS 04/12/17 W Wood smoke Smoldering N/A N/A 1187 N/A 19-65 290-326 DTT,OHP,PAN,GC-MS 07/02/17 E Gasoline LNOX 20.0 470 (166) 212 29.8 f 14-50 297-324 DTT,OHP,PAN,GC-MS 05/29/17 E Toluene HNOX 4.5 764 (163) 254 11.5 16-54 296-320 DTT,OHP,PAN 05/29/17 W Toluene LNOX 5.2 319 (75) 280 13.9 26-64 297-316 DTT,OHP,PAN 09/19/17 E Toluene LNOX 7.6 609 (235) 344 13.6 11-47 292-322 FTIR 08/16/17 E Isoprene HNOX 15.0 3300 388 4.6 15-50 297-327 DTT,OHP,PAN 08/16/17 W α-Pinene LNOX 3.4 141 386 20.1 25-60 297-319 DTT,OHP,PAN a 380 “E” represents the east chamber and “W” represents the west chamber. b 381 Wood smoke was produced under either high-temperature (High-Temp) or smoldering combustion condition. SOA was 382 formed from the photooxidation of precursors under either high-NOx (HNOX) or low-NOx (LNOX) condition. c 383 [HC]0 represents the initial mixing ratios of HCs in ppmC. d 384 N/A represents “not applicable”. e 385 [NOx]0 represents the initial mixing ratios of NOx. For photooxidation experiments of gasoline and toluene, HONO 386 generated from the reaction of 0.1 M NaNO2 and 10% w/w H2SO4 was injected to the chamber as a source of OH radicals. 387 The concentration of HONO was estimated using the decrease of NO2 signal in the presence of a base denuder (coated 388 with 1% Na2CO3+1% glucose). f 389 The SOA yield of gasoline was calculated using the maximum SOA concentration divided by the total consumption of 390 aromatic HCs, including toluene, (o, m, p)-xylene, 1,3,5-trimethylbenzene and 1,2,4-trimethylbenzene. g 391 The RH and temperature conditions for each experiment were recorded from sunrise to the collection of the final sample. h 392 The SOA samples were applied to DTT assay, organic hydroperoxides analysis (OHP), PAN analysis, GC-MS analysis, 393 or FTIR analysis. 394

20


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395 396 397 398 399 400 401

Figure 1. (a) The DTTm of wood smoke particles (high-temp combustion and smoldering combustion). The lines in each figure represent the time-based linear regression of initial DTT consumptions. (b) The aging effect on DTTm, OHP and PAN. The grey-dash line represents the completion of chemical injection into the chamber. (c) DTTm from OHP and PAN.

21



402 403 404 405 406 407 408

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Figure 2. (a) The DTTm of SOA derived from gasoline, toluene, isoprene and α-pinene under different NOx conditions (HNOX: high NOx, LNOX: low NOx). The lines in each figure represent the timebased linear regression of initial DTT consumptions. (b) The aging effect on DTTm, OHP and PAN. The grey-dash line represents the completion of chemical injection into the chamber. (c) DTTm from OHP and PAN.

22


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409 410 411 412


Figure 3. The time profiles of quinones (including PQN and AQN) concentrations in wood smoke particles measured using GC-MS.

413 414 415 416 417 418 419

Figure 4. (a) The concentrations of functional groups in LNOX-toluene (09/19/17) SOA at 15:00 EST were estimated using FTIR spectral data except for OHP (NPBA assay). (b) The comparison of DTTm and chemical compositions of LNOX-toluene SOA. The quantities of PAN and OHP in the SOA at 15:00 were estimated using the interpolation between the corresponding values at 13:30 EST and 15:50 EST. The concentration of electron-deficient alkenes was estimated by decoupling the FTIR spectrum.

420

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